Quantitative correlation between rock fall and weather seasonality to predict changes in rock fall hazard with climate change

The Canadian Cordillera in the province of British Columbia witnesses numerous rock falls every year. Studies on the recorded rock fall data in this area show that rock fall hazard follows weather conditions, especially precipitation and freeze-thaw cycles. This relationship indicates that a weather-based approach can be implemented to estimate possible changes in the rock fall hazard due to climate change. In this paper, we used a statistical approach to quantify the relationship between monthly weather averages and rock fall frequencies for a section of a transportation corridor along the Fraser River in British Columbia, Canada. In this regard, von Mises distributions are used to find the best-fitted models to the monthly precipitation and freeze-thaw cycles, and proper relative weights are applied to the models in order to calibrate them to the rock fall monthly frequency. The calibrated model is used with input data from climatic predictions for 2041-2070 and 2071-2100 to see how rock fall distribution will be affected due to climate change in the future decades. Results show that between 9 and 19%, more rock fall is anticipated in future winters. Rock falls are expected to decrease in other months, especially in October, November, March, and April. This paper presents a method to predict changes in rock fall hazard seasonality due to climate change and illustrates the method with a case study along a section of the Canadian Cordillera.

Automated summary

Studies have shown that the Canadian Cordillera in British Columbia experiences numerous rock falls annually, and these incidents are influenced by weather conditions, especially precipitation and freeze-thaw cycles. This research uses a statistical approach to quantify the relationship between weather data and rock fall frequencies, and predicts future changes in rock fall hazard due to climate change.